A working guide to AI-assisted agency delivery.
Explore AI-assisted agency delivery, with practical workflows, a working example and checks for common mistakes.
Explore the guide ↗The working guide
AI / 10 SECTIONSAI for Agencies is a focused resource for agency project and production leads, exploring AI-assisted agency delivery through the work people actually need to perform. For this topic, the workflow is to agree acceptable uses, separate client data from experiments, and review deliverables. This guide uses an agency AI delivery policy to hold the decisions together and examines client permissions, output ownership questions and human approvals as distinct quality concerns.
The example involves an agency testing AI support for an internal draft brief; it is an illustrative exercise for this subject, rather than a reported client result. Agency AI use needs agreement about acceptable input and review. Separate experiments from client delivery, and make sure account teams understand how confidential client material may be handled before production begins.
Start by describing the task that makes AI-assisted agency delivery relevant now. Use the situation of an agency testing AI support for an internal draft brief to identify the practical question before choosing a method. A concern involving client permissions may require different evidence from a concern involving output ownership questions.
Keep those questions visible in an agency AI delivery policy, alongside the intended outcome. The scope of AI-assisted agency delivery becomes easier to discuss when an agreed requirement is clearly distinguished from an idea that still needs investigation. Before proceeding with AI-assisted agency delivery, decide whether the current state of human approvals creates a dependency that needs another person's input.
An agency AI delivery policy
Use an agency AI delivery policy as a shared reference for this piece of AI-assisted agency delivery. The record is especially useful when agency project and production leads need to explain why a particular route was chosen. Connect the entry about client permissions to the relevant evidence for AI-assisted agency delivery, rather than copying information without its source context.
Review an agency AI delivery policy after a meaningful change; an abandoned reference can mislead the next person working on AI-assisted agency delivery.
Agree acceptable uses
The first working stage is to agree acceptable uses. In the example involving an agency testing AI support for an internal draft brief, identify which input is needed before this action can produce a dependable result. Consider how questions about client permissions affect the starting conditions for the action to agree acceptable uses, including information that has not been confirmed.
Record the outcome in an agency AI delivery policy and explain any limitation before asking somebody to separate client data from experiments. This creates a traceable starting point for AI-assisted agency delivery, making an incomplete input easier to recognise before it influences the rest of the work.
Separate client data from experiments
Continue by deciding how to separate client data from experiments under the agreed conditions. The handoff from the first stage of AI-assisted agency delivery should contain the information this action actually requires. Before you separate client data from experiments, inspect output ownership questions and identify any assumption that has become doubtful.
If the situation involving an agency testing AI support for an internal draft brief reveals a different requirement, update an agency AI delivery policy before expanding the work. A visible change decision keeps AI-assisted agency delivery coherent and helps the next participant understand whether the original scope still applies.
Review deliverables
The third stage is to review deliverables, bringing the current piece of AI-assisted agency delivery to an understandable state. Check human approvals against the agreed purpose of AI-assisted agency delivery, not merely against a list of completed activities. Use an agency AI delivery policy to identify follow-up responsibilities and relevant limits.
In the example of an agency testing AI support for an internal draft brief, ask what the receiving person would need before relying on the output. Closing this stage of AI-assisted agency delivery clearly prevents an unfinished dependency from being mistaken for an accepted result.
Avoid using client material in tools without agreed safeguards
06 / 10A specific failure pattern in AI-assisted agency delivery is using client material in tools without agreed safeguards. It can create a gap between the appearance of progress and the actual outcome needed by agency project and production leads. Check whether client permissions was understood before the action began and whether output ownership questions was examined by somebody with the relevant context.
Capture the correction in an agency AI delivery policy, including its effect on human approvals. The aim is to reduce the opportunity for using client material in tools without agreed safeguards to recur, while keeping the process proportionate to the work.
Work through a realistic situation
Consider an agency testing AI support for an internal draft brief as a small rehearsal of AI-assisted agency delivery. Write down the request and expected result, then identify who performs the action to agree acceptable uses. Before moving to the instruction to separate client data from experiments, ask which information the next participant needs.
Use an agency AI delivery policy to preserve any question the example exposes, especially where client permissions is uncertain. Then decide how to review deliverables without hiding a concern about human approvals.
Check human approvals
The review criteria for this guide are client permissions, output ownership questions and human approvals. Examine each criterion separately in the context of AI-assisted agency delivery, because a positive finding in one area does not settle the other questions. For agency project and production leads, a useful review records what was examined and how the finding affects the next action.
Connect the evidence to an agency AI delivery policy, including any limitation in the material available. In the situation involving an agency testing AI support for an internal draft brief, identify which finding would prevent a responsible handover. This approach makes the review of AI-assisted agency delivery explainable, rather than treating an unexplained approval label as evidence that the task is ready.
Maintenance of AI-assisted agency delivery should respond to changes in the task, its inputs and its responsible people. Assign an owner to an agency AI delivery policy and explain which events should trigger another review. A changed assumption about client permissions may affect the earlier decision to agree acceptable uses; a concern about human approvals may require a new closing check.
Remove obsolete directions from an agency AI delivery policy deliberately so that earlier versions do not compete with approved guidance. When output ownership questions changes, explain whether the instruction to separate client data from experiments needs different inputs or a revised decision.
Choose a practical next step
Begin with one bounded task involving AI-assisted agency delivery rather than a complete redesign of the surrounding operation. Prepare an agency AI delivery policy, work through the three actions and inspect the result using the criteria for client permissions, output ownership questions and human approvals. Ask someone from the intended audience of agency project and production leads to identify a point that still needs clarification.
Compare that observation with the example of an agency testing AI support for an internal draft brief, then choose a specific change worth testing.